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etcher, dedicated Plassys evaporator, ALD and PE-CVD machines, etc.). The Institut NEEL, UPR 2940 CNRS, is one of the largest French national research institutes for fundamental research in condensed
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machine learning tools. The postdoctoral fellow will contribute to various aspects of the project, such as: * developing new theoretical and numerical approaches for determining the thermodynamic and
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physics groups, as well as the DELPH (Detection and Lasers for Physics) and GTA (Acquisition Techniques Group) groups. The Physics Division is composed of 25 permanent physicists, around 20 PhD students and
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. - Knowledge in programming, data treatment, electron diffraction simulations, mathematical skills, knowledge about machine learning and artificial intelligence is a plus. Website for additional job details
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Information Eligibility criteria - PhD in functional ecology - Good command of the following subjects: functional ecology, root system ecology, organism diversity, soil and ecosystem functioning - Very good
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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copolymers, which will then be evaluated for their degradability and mechanical properties. Using active learning, a branch of AI, the research will be guided through the large parameter space of copolymers
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the synthesis of the nanowires and their assembly into networks (by soft chemistry), while the synthesis of the matrix (CVD deposition) will mainly be carried out by a PhD student already recruited
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departments (from Paris-Saclay university and from Université Lyon 1), and involves 7 PIs and 5 postdocs and PhD students devoted to distinct workpackages of the project. The postdoc will be based at EGCE